- Title
- Estimation of 1/f noise
- Creator
- Ninness, Brett
- Relation
- IEEE Transactions on Information Theory Vol. 44, Issue 1, p. 32-46
- Publisher Link
- http://dx.doi.org/10.1109/18.650986
- Publisher
- Institute of Electrical and Electronics Engineers
- Resource Type
- journal article
- Date
- 1998
- Description
- Several models have emerged for describing 1/fγ noise processes. Based on these, various techniques for estimating the properties of such processes have been developed. This paper provides theoretical analysis of a new wavelet-based approach which has the advantages of having low computational complexity and being able to handle the case where the 1/fγ noise might be embedded in a further white-noise process. However, the analysis conducted here shows that these advantages are balanced by the fact that the wavelet-based scheme is only consistent for spectral exponents γ in the range γ∈(0, 1). This is in contradiction to the results suggested in previous empirical studies. When γ∈(0, 1) this paper also establishes that wavelet-based maximum-likelihood methods are asymptotically Gaussian and efficient. Finally, the asymptotic rate of mean-square convergence of the parameter estimates is established and is shown to slow as γ approaches one. Combined with a survey of non-wavelet-based methods, these new results give a perspective on the various tradeoffs to be considered when modeling and estimating 1/fγ noise processes.
- Subject
- 1/fγ noise processes; wavelet-based approach; white-noise process
- Identifier
- http://hdl.handle.net/1959.13/26359
- Identifier
- uon:851
- Identifier
- ISSN:0018-9448
- Rights
- Copyright © 1998 IEEE. Reprinted from IEEE Transactions on Information Theory.
- Language
- eng
- Full Text
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